Planning always means handling uncertainty. Organizations want to avoid uncertainty as good as possible, and they use planning as a means to achieve that. A frequent misunderstanding in doing so is that a more detailed planning automatically means a more accurate planning. The opposite can be the case.

 There’s an old but still very true rule on the granularity of planning: 

“Planning without control is useless,
control without planning is impossible”

Wild: Grundlagen der Unternehmensplanung (1981), S. 44.

It is meaningless to plan things that will not be used for later control. At the same time, if we want to  control something, we should plan it beforehand to have a proper baseline. So planning implies that the resulting data will at a later stage be used to measure actual developments against it. This is mainly done for three reasons:

1. One reason is to gain insights that support future decisions, like for example: Why have we missed the planned EBIT? What parts of our organization went wrong? What products did not bring the expected margins? Why did our personnel costs exceed budget?
2. On the other hand, planning data are typically also used as targets for organizational units and their responsible owners. Benefits and bonuses might be bound to their achievement. Planning data are then supposed to motivate employees to reach the expected numbers.
3. Asking employees to plan certain topics has a behavioral effect in itself. If you ask a sales person to plan revenues by key account, you will focus his attention on how to win contracts with these customers in the upcoming year.

These different objectives of planning and controlling need to be considered when we talk about the suitable granularity of planning. If planning is done on a level of detail which is not needed for any of these reasons, it is inefficient. To give an example: A rolling 12-month-forecast of canteen costs will most probably not add significant value to your organization, as you will not analyze cost deviations on that level. If you will not set such detail targets and you do not want to explicitly force anyone to focus his attention on that level, this planning granularity has to be seriously questioned.

It is a common misunderstanding that adding detail to planning reduces risks and makes planning more accurate.

It is a dangerous mistake to mix up detail with accuracy. Forcing people to plan too detailed can even lead to the opposite effect. Just take the following very simple example as a basis. It shows how adding detail to sales planning will cause the amount of data that have to be delivered to skyrocket:

Asking a person to fill in 12.000 or 120.000 cells in an excel sheet with meaningful numbers will not cause him or her to really think about the figures that are input. Involved parties have only got a limited time for the generation of planning data. The more lines they need to fill, the less time will be spent per line. The operational job of capturing data will take the lead over really thinking what numbers can be achieved in the next year. And this in fact reduces the validity of the resulting data, even though they have been captured on an impressive granularity level and many plan-actual-comparisons will be possible in the next fiscal year. But as the validity of these numbers is limited, so are any plan/actual-comparisons that will be performed on their basis.

Mixing up detail with accuracy or even data quality is what we consider the Detail Trap of Planning. It is one of the reasons why even modern system implementations are too complex compared to the value they actually create. Not to get this wrong: Detail is not always bad, but detail added for the wrong reasons surely is.

Take part in Benchmark 2017

You want to evaluate and improve your planning processes? You want to find out how you are positioned compared to other companies? The University of Applied Sciences in Rosenheim is about to start an international Benchmarking study on corporate planning processes in cooperation with SAP and Stampa Partners.

The Benchmark 2017 study evaluates planning processes with the help of a detailed and structured online survey. Results are analyzed along a sophisticated maturity model and compared to benchmark companies. Every participating organization will receive an individualized summary of its results as well as an evaluation of its planning maturity. A working paper on the digitalization of planning processes will give valuable insights into improvement potentials. It points to concrete options on how to re-engineer traditional structures and how to transform these into effective and efficient processes.

Participation in Benchmark 2017 is open for companies of all industries and sizes. Organizations can benefit independent of their current professionalism in planning and independent of the software tools that are currently used. All data are handled confidentially within the supervisory university. Individual results are anonymized before they flow into the overall benchmark.

More information: www.benchmark2017.com